Effectiveness of digital health interventions on blood pressure control, lifestyle behaviours and adherence to medication in patients with hypertension in low-income and middle-income countries: a systematic review and meta-analysis of randomised controlled trials

Summary Background Digital health interventions can be effective for blood pressure (BP) control, but a comparison of the effectiveness and application of these types of interventions has not yet been systematically evaluated in low- and middle-income countries (LMICs). This study aimed to compare the effectiveness of digital health interventions according to the World Health Organisation (WHO) classifications of patients in terms of BP control, lifestyle behaviour changes, and adherence to medication in patients with hypertension in LMICs. Methods In this systematic review and meta-analysis, we searched the PubMed, Scopus, Web of Science, Embase, CINAHL, and Cochrane Library databases for randomised controlled trials (RCTs) published in English, comprised of adults (≥18 years old) with hypertension and the intervention consisted of digital health interventions according to WHO's classifications for patients in LMICs between January 1, 2009, and July 17, 2023. We excluded RCTs that considered patients with hypertension comorbidities such as diabetes and hypertension-mediated target organ damage (HMTOD). The references were downloaded into Mendeley Desktop and imported into the Rayyan web tool for deduplication and screening. The risk of bias was assessed using Cochrane Risk of Bias 2. Data extraction was done according to Cochrane's guidelines. The main outcome measures were mean systolic blood pressure (SBP) and BP control which were assessed using the random-effect DerSimonian-Laird and Mantel-Haenszel models. We presented the BP outcomes, lifestyle behaviour changes and medication adherence in forest plots as well as summarized them in tables. This study is registered with PROSPERO, CRD42023424227. Findings We identified 9322 articles, of which 22 RCTs from 12 countries (n = 12,892 respondents) were included in the systematic review. The quality of the 22 studies was graded as high risk (n = 7), had some concerns (n = 3) and low risk of bias (n = 12). A total of 19 RCTs (n = 12,418 respondents) were included in the meta-analysis. Overall, digital health intervention had significant reductions in SBP [mean difference (MD) = −4.43 mmHg (95% CI −6.19 to −2.67), I2 = 92%] and BP control [odds ratio (OR) = 2.20 (95% CI 1.64–2.94), I2 = 78%], respectively, compared with usual care. A subgroup analysis revealed that short message service (SMS) interventions had the greatest statistically significant reduction of SBP [MD = −5.75 mm Hg (95% Cl −7.77 to −3.73), I2 = 86%] compared to mobile phone calls [MD = 3.08 mm Hg (−6.16 to 12.32), I2 = 87%] or smartphone apps interventions [MD = −4.06 mm Hg (−6.56 to −1.55), I2 = 79%], but the difference between groups was not statistically significant (p = 0.14). The meta-analysis showed that the interventions had a significant effect in supporting changes in lifestyle behaviours related to a low salt diet [standardised mean difference (SMD) = 1.25; (95% CI 0.64–1.87), I2 = 89%], physical activity [SMD = 1.30; (95% CI 0.23–2.37), I2 = 94%] and smoking reduction [risk difference (RR) = 0.03; (95% CI 0.01–0.05), I2 = 0%] compared to the control group. In addition, improvement in medication adherence was statistically significant and higher in the intervention group than in the control group [SMD = 1.59; (95% CI 0.51–2.67), I2 = 97%]. Interpretation Our findings suggest that digital health interventions may be effective for BP control, changes in lifestyle behaviours, and improvements in medication adherence in LMICs. However, we observed high heterogeneity between included studies, and only two studies from Africa were included. The combination of digital health interventions with clinical management is crucial to achieving optimal clinical effectiveness in BP control, changes in lifestyle behaviours and improvements in medication adherence. Funding None.


Introduction
Globally, approximately 1.28 billion people are living with hypertension as the second leading risk factor for premature death. 1,2Current guidelines recommend a blood pressure (BP) of 140/90 mmHg or more persistently for the diagnosis of hypertension in adults. 3Hypertension is a major cause of cardiovascular disease (CVD), and kidney disease and BP control reduce the risk of these complications. 3,4Despite the availability of effective hypertensive medications, BP treatment and control rates remain low, especially in low-and middleincome countries (LMICs). 4Self-management education, including education for patients, self-monitoring of clinical measurements, 5 lifestyle modifications (e.g., healthy diet, physical activity, weight loss, smoking cessation, and alcohol reduction), 6 and support for

Research in context
Evidence before this study Digital health interventions have shown favourable findings for blood pressure (BP) control.We searched PUBMED, the Cochrane Library, and the PROSPERO database from the start to May 16, 2023, using the search terms ("hypertension" OR "blood pressure" OR "high blood pressure") AND ("telemedicine" OR "text messaging" OR "electronic health" OR "mobile health" OR mHealth OR "digital health") AND ("blood pressure control" OR "blood pressure management" OR "hypertension control" OR "hypertension management" OR "medication adherence" OR "smoking cessation" OR "alcohol abstinence" OR "weight loss" OR "diet therapy" OR "behaviour modif*" OR "physical activit*") AND ("randomized controlled trial" OR "controlled trial" OR "trials") to identify meta-analyses that compared the effectiveness of digital health intervention in adult patients with hypertension, according to World Health Organisation (WHO) classifications, in low-and middle-income countries (LMICs).We found a 2019 meta-analysis of individual global data (n = 4271 respondents) showing that digital health interventions reduced both systolic and diastolic BP in patients with hypertension compared with usual care.That review was limited by the small number of included studies (eleven) and a small pooled sample size (4271), did not compare the effectiveness of digital health interventions according to WHO's classifications for patients and included the majority of the studies from high-income countries.Furthermore, due to rapid innovations in telecommunications, several studies have been published recently in LMICs that have not been included in those reviews and did not compare which type of digital health intervention according to WHO's classifications for patients is effective in LMICs.

Added value of this study
To our knowledge, this is the first meta-analysis to compare digital health interventions according to WHO's classifications for patients and report on their effectiveness on BP control, lifestyle behaviour changes, and medication adherence in adult patients with hypertension in LMICs using only randomised controlled trials (RCTs).We found that digital health interventions may be effective in reducing systolic blood pressure (SBP) and BP control in adult patients with hypertension, regardless of the three methods of delivery in LMICs.The meta-analysis also showed that the interventions had a significant effect in supporting changes in lifestyle behaviours related to a low-salt diet, physical activity and smoking reduction as well as improvement in medication adherence compared to the control group.However, we observed high heterogeneity between included studies, and only two studies from Africa were included.
Implications of all the available evidence Since a minimum of 92% of the worldwide population has access to several digital health devices, physicians should familiarise themselves with this method of intervention delivery and encourage patients with hypertension to use scientific digital health devices to improve their BP control.The combination of digital health interventions with clinical management is fundamental to achieving optimal clinical effectiveness in BP control.medication adherence, has been extensively used for BP control. 7n recent years, digital health interventions have become a very effective, useful and available form of healthcare delivery in self-management and controlling hypertension, [8][9][10][11][12] compared with usual care.Digital health interventions, also known as "a discrete functionality of digital technology that is applied to achieve health objectives", have exceptional potential to promote universal health coverage and enhance health service delivery by improving the accountability, availability, accessibility, continuity, utilization, and effectiveness of health care. 13,14The World Health Organisation (WHO) classifies digital health interventions according to types of users (for patients, healthcare providers and data services) to cover various areas of health systems with a particular focus on health service delivery. 15One of the WHO's classifications of digital health interventions for patients includes short message service (SMS), multimedia message services (MMS), interactive voice response or phone calls, web-based/online telecare platforms and smartphone applications. 15Data show that out of 6.9 billion of the global population, 86% have access to smartphones, 92% use orthodox mobile phones, and 64% have internet access. 16ne area that has great potential for improvements through digital health interventions is the management of non-communicable diseases (NCDs), including hypertension, in primary health care. 13This is because NCDs, particularly hypertension, are characterized by long disease durations and a continuous need to anticipate and alleviate risk factors through lifestyle modifications, which is better addressed by primary health care than higher-level health facilities. 17Several metaanalyses reported that digital health interventions reduced both systolic BP and diastolic BP in individuals with hypertension compared with face-to-face delivery. 16,18,19However, those meta-analyses were inadequate due to the smaller number of studies included from LMICs and the smaller combined sample size.People living in LMICs, such as many countries in Africa, are at high risk of many health conditions compared to those living in high-income countries while having the most limited access to health innovations such as digital health intervention. 20urthermore, due to rapid innovations in telecommunications, several studies have been published recently in LMICs that have not been included in those reviews.Most importantly, although some types of digital health interventions, such as SMS, MMS, interactive voice response or phone calls, web-based/online telecare platforms and smartphone applications, have been used to provide interventions, no study has compared their effectiveness and application to assist reasonable decisions in LMICs.To enable physicians to choose the digital health interventions most effective for BP control, changes in lifestyle behaviours, and improvement in medication adherence, we aimed to compare digital health interventions according to WHO's classifications for patients and report on their effectiveness on BP control, change in lifestyle behaviours, and improvement in medication adherence in adult patients with hypertension in LMICs using only randomised controlled trials (RCTs).

Search strategy and selection criteria
This systematic review and meta-analysis followed and adhered to the appropriate reporting guidelines of the 2020 PRISMA. 21The protocol that was followed is registered in PROSPERO, CRD42023424227.The PubMed, Scopus, Web of Science, Embase, CINAHL, and Cochrane Library databases were searched for RCTs published in English using keywords and MeSH terms.The search strategies were maximized to identify articles on patients with hypertension.The searches were limited between January 1, 2009, and July 17, 2023.The reason is that 2009 was designated as the year digital health intervention started to become broadly embraced. 16The complete search strategies are presented in the Supplementary File (Table S1 on pages 1-5).We manually searched the reference lists of relevant studies on digital health interventions among patients with hypertension.All references from database searches were downloaded into Mendeley Desktop version 1.19.8.The references were imported from Mendeley into the Rayyan web tool for the removal of duplicates and the remaining articles for eligibility by three authors (LST, AD and VB).
The inclusion criteria were as follows: (1) the population comprised adults (≥18 years old) with hypertension; and (2) the intervention consisted of digital health interventions according to WHO's classifications for patients, 13 to provide reminders to patients during follow-up to assess BP control, behaviour changes and adherence to medication as well as preventive healthcare services (Table 1 ranking and published in English were considered for inclusion. 39We excluded RCTs that considered patients with hypertension comorbidities such as diabetes and hypertension-mediated target organ damage (HMTOD), such as strokes, hypertensive heart disease, ischaemic heart diseases, retinopathy and chronic kidney disease.][42][43] Additionally, studies that did not use digital health interventions according to the WHO's classifications for patients were excluded. 13

Data analysis
Three authors (LST, AD and VB) developed a comprehensive data extraction form according to the guidelines led in the Cochrane Handbook. 44We extracted the data, such as authors' The relevant study characteristics, results, intervention and reports on the effectiveness of the intervention were summarized.The intervention was categorised as effective if the digital health intervention had statistically significant (p ≤ 0.05) effects compared to usual care and considered ineffective if no significant differences were found between the main outcomes (p ≥ 0.05).The main outcome was mean SBP (and 95% Cl) and BP control.The secondary outcomes were changes in lifestyle behaviours (diet, physical activity, weight loss, body mass index, smoking reduction, alcohol reduction and general quality of life) and improvement in medication adherence.
The quality of the studies was assessed by three authors (LST, AD and VB) using the reviewed Cochrane risk-of-bias 2. 45 These are selection bias (random sequence generation and allocation concealment); performance bias (blinding of respondents and personnel); detection bias (blinding of outcome assessment); attrition bias (incomplete outcome data); reporting bias (selective reporting); and bias that emerges from period and carryover effects (for crossover studies). 45Any disagreements were resolved by the fourth author FA (Supplementary File, Figs.S1 and S2, on pages 18 and 19).
STATA Version 17, R Version 4.3.2 and Review Manager Version 5.4.1 were used for the analyses.The I 2 statistic and Cochran's Q test were used to assess heterogeneity.Depending on the heterogeneity of the data, random-effect (for I 2 ≥ 50%) or fixed-effect (for I 2 < 50%) models were used.Effect sizes for continuous outcomes were calculated using the mean difference (MD) for SBP and DBP and the standardised mean difference (SMD) and risk difference (RR) for lifestyle behavioural and medication adherence outcome measurements.Effect sizes for dichotomous outcome measurements were calculated using the odds ratio (OR) for BP control, lifestyle behaviour and medication adherence.Subgroup analyses by different modes of digital health intervention, duration of digital health intervention, year of publication and income economies were performed to determine potential sources of heterogeneity.Sensitivity analyses were performed to determine the strength of the pooled estimates and whether a single study was responsible for the outcomes.Funnel plots were used to assess publication biases visually and statistically by Egger's and Begg's tests for confirmation at p ≤ 0.05.

Role of the funding source
There was no funding source for this study.VB, AD and FA had access to the dataset and had final responsibility for the decision to submit it for publication.

Results
The database searches returned 9315 articles, and an additional 7 articles were found through manual searching of reference lists of pertinent articles.We removed 3640 duplicates, 5682 titles and abstracts were screened, 5519 records were excluded together with articles without full texts, 163 full texts were assessed for eligibility, and 141 that focused on people with other health conditions and other reasons listed were excluded.Finally, 22 studies on adult patients with hypertension were captured in the systematic review (Fig. 1).

Assessment of bias of the articles included
Out of 22 articles included, 7, three and 12 were categorised as high risk, having some concerns, and low risk of bias, respectively.Three articles were considered to have a high risk of bias for the randomization procedure. 8,11,32One study assigned respondents before allocation concealment, 32 and two provided partial information about random sequence generation. 8,11Four deviated from the proposed intervention, without blinding the respondents and personnel to the intervention task, 11,22,24,28 ; however, such blinding is usually not feasible in digital health interventions.Two articles did not report on the blinding of respondents. 22,24Five articles reported high attrition biases due to missing data. 10,11,23,28Four articles acquired a high risk of bias categorisation for adopting a selective reporting of results, lack of information on sufficient training of personnel for the assessment of results, or not stating if results evaluators were mindful of respondents' intervention task. 23,24,26Regarding the choice of reported outcomes, two articles provided incomplete result assessments of data analysis, causing a high risk of bias. 11,26enerally, the majority of the SMS intervention articles were measured as low risk, but most of the smartphone apps and mobile phone call intervention articles were evaluated as high risk (Supplementary File, Figs.S1 and S2, on pages 18 and 19).

Meta-analysis
Nineteen studies (n = 12,418 participants) were included in the meta-analysis, [8][9][10][11][12][22][23][24][25][26][27][28][29][30][31]34,[36][37][38] and 5 out of 19 were measured as having a high risk of bias. 8,11,22,24,28 wo studies reported two interventions against the same outcome assessed.8,32 Blood pressure The study by, 8 reported two interventions against the same outcome assessed and included in the metaanalysis of SBP.Therefore, 20 interventions were reported on the forest plot of SBP, [8][9][10][11][12][22][23][24][25][26][27][28][29][30][31]   groups was not statistically significant (p = 0.14). The poled heterogeneity across the studies was significant (Q = 239.3;p < 0.0001) and high (I 2 = 92.1%).Mobile phone call studies (I 2 = 87.7%)and SMS studies (I 2 = 86.2%)showed larger heterogeneity than smartphone app studies (I 2 = 79.4%)(Fig. 2 2: Forest plot of the mean difference in SBP between the intervention and control groups.Forest plot of mean difference in systolic blood pressure (SBP) (expressed as mm Hg) between the digital health intervention and the control groups, and subgroup analysis by mode of delivery of the intervention (Mobile phone call, Short message service (SMS) and Smartphone app).The size of the blue squares indicates the weight of the evidence from each of the studies.Studies with CI (horizontal line) crossing zero (vertical line) are inconclusive.Studies with more participants have narrower CIs. Te red diamonds represent the summary effect sizes in each of the subgroups and the green the overall sample, with the width of the diamond indicating the 95% CI.A statistically significant greater reduction in SBP is seen in the intervention group, compared with the control group in the overall sample and with the two modes of delivery (SMS and smartphone app).SMS interventions displayed the greatest reduction, compared with smartphone apps and mobile phone calls, but the differences between the three modes were not significant.The data present high heterogeneity.

Weight loss
A total of 2 studies out of 22 evaluated the effectiveness of digital health interventions on weight loss.The meta-analysis of continuous outcome measurements for weight loss of 2 studies showed no significant differences in the intervention [SMD = −0.04;(95% CI −0.58 to 0.49); p = 0.87; n = 408] compared to the control group, 34,35 (Supplementary File, Fig. S6, on page 21).

Reduction in body mass index
A total of 4 studies out of 22 assessed the effectiveness of digital health interventions on body mass index (BMI).The meta-analysis of continuous outcome measurements for BMI of 4 studies showed no significant differences in the intervention [SMD = −0.13;(95% CI −0.28 to 0.02); p = 0.09; n = 698] compared to the control group, 23,26,33,34 (Supplementary File, Fig. S7, on page 22).
Fig. 4: Meta-analysis of continuous outcome measurements for low-salt diets.Forest plot of standard mean difference for low-salt diets between the digital health intervention and the control groups.The size of the green squares indicates the weight of the evidence from each of the studies.Studies with CI (horizontal line) are inconclusive.The black diamonds represent the summary effect sizes in the overall sample, with the width of the diamond indicating the 95% CI.A statistically significant greater reduction for low-salt diets is seen in the intervention group, compared with the control group.The data present high heterogeneity.
Fig. 5: Meta-analysis of continuous outcome measurements for PA.Forest plot of standard mean difference for physical activity (PA) between the digital health intervention and the control groups.The size of the green squares indicates the weight of the evidence from each of the studies.Studies with CI (horizontal line) crossing zero (vertical line) are inconclusive.The black diamonds represent the summary effect sizes in the overall sample, with the width of the diamond indicating the 95% CI.A statistically significant greater reduction for PA is seen in the intervention group, compared with the control group.The data present high heterogeneity.

Alcohol reduction
A total of 3 studies out of 22 assessed the effectiveness of digital health interventions on alcohol reduction.The meta-analysis of dichotomous outcome measurements for alcohol reduction in 3 studies revealed no significant differences in the intervention [RR = 0.01; (95% CI −0.01 to 0.04); p = 0.26; n = 4411] compared to the control group, [35][36][37] (Supplementary File, Fig. S8, on page 22).
Fig. 6: Meta-analysis of dichotomous outcome measurements for smoking reduction.Forest plot of risk difference for smoking reduction between the digital health intervention and the control groups.The size of the blue squares indicates the weight of the evidence from each of the studies.Studies with CI (horizontal line) crossing zero (vertical line) are inconclusive.The black diamonds represent the summary effect sizes in the overall sample, with the width of the diamond indicating the 95% CI.A statistically significant greater reduction in smoking reduction is seen in the intervention group, compared with the control group.The data present no heterogeneity.

Sensitivity analyses
Sensitivity analyses to determine the strength of the pooled effect for the SBP and DBP results were performed.We sequentially removed each study to assess whether the direction of associations was influenced by a single large study with a positive outcome.For the SBP outcome, the direction of associations did not change with the removal of any of the study datasets, with the

Publication bias
Publication biases were determined visually by funnel plots.The forest plots for both SBP and DBP showed slight asymmetry and more symmetric dispersal, respectively (Figs. 3 and 6).These results were confirmed statistically by Egger's and Begg's tests.For SBP, Egger's test (p = 0.47) and Begg's test (p = 0.92) and for DBP, Egger's test (p = 0.39) and Begg's test (p = 0.59).Therefore, either the SBP or the DBP funnel plot specified publication bias (Supplementary File, Figs.S6 and S7, on pages 26 and 27).

Discussion
This study presents the comparative effectiveness and application of digital health interventions according to the WHO's classifications for patients and reports on their effectiveness in BP control, changes in lifestyle behaviours, and improvements in medication adherence in adult patients with hypertension in LMICs.The meta-analysis of 19 studies (n = 10,461 respondents) resulted in better BP control, with a significant reduction in SBP and DBP by 4.43 mm Hg and 2.06 mm Hg, respectively, compared with the control.The decreases in SBP and DBP were scientifically significant.First, it confirmed that digital health was effective in controlling and managing hypertension, medication adherence, healthy lifestyles and body composition. 50,51According to the Blood Pressure Lowering Treatment Trialists' Collaboration analysis of 29 RCTs, a reduction in SBP and DBP of 2 mmHg would remarkably decrease the prevalence of CVD by 10%. 18Our findings are consistent with previous meta-analyses performed among patients with hypertension.A study of 12 RCTs showed that digital health intervention produced greater reductions in SBP by 3.96 and DBP by 1.85 mm Hg than the control. 19A meta-analysis of 11 RCTs revealed that digital health intervention resulted in a remarkable decrease in SBP by 3.85 mmHg and in DBP by 2.19 mmHg compared to usual care. 52Similarly, a study with global individual data (n = 7092 respondents) confirmed that digital health intervention provides a notable reduction in SBP by 3.62 and DBP by 2.45 mm Hg compared with the control. 16The similarity across the studies could be attributed to the inclusion of some respondents on antihypertensive drugs.
When comparing the three various methods of delivery, we found that SMS and smartphone apps were more effective in terms of BP control than phone call interventions due to the small number of phone call RCT studies.However, SMS presented the highest reduction in SBP and DBP compared with smartphone app interventions.In contrast, a study by Siopis et al., 16 comparing the efficacy of SMS, smartphone app, and website interventions on improving BP in adult patients with hypertension found that smartphone app and website interventions provided a greater remarkable reduction in SBP and DBP compared with SMS interventions.The disparities between these studies are that our study was centred on LMICs, whereby more people cannot afford smartphones with applications, compared with the study by Siopis et al., 16 which assessed digital health interventions globally.Second, due to challenges in accessing internet services, more people in LMICs own a telephone with SMS capacity compared to smartphones. 16In LMICs, cell phone penetration has surpassed 90% in recent years, and mobile internet connectivity is approximately 40%. 53hird, SMS might be more user-friendly and easier to access due to the convenient and portable nature of mobile phones, especially in LMICs, compared to smartphone apps or websites that might require knowledge to operate and access networks.Even those with smartphones find it difficult to use the applications frequently because of the high cost of data.However, the reduction in SBP and DBP due to smartphone application in our systematic review might reflect patients' preferences and their affordability of data and internet services.Additionally, the satisfactoriness of SMS and smartphone app interventions by patients with hypertension has been established in healthcare delivery. 12,54e found the odds of BP control to be 2.20 times greater in the delivery of digital health intervention compared to usual care.Similarly, a study by Li et al., 19 found the odds of BP control to be 1.42 times higher in the delivery of digital health intervention compared to usual care.Kassavou et al., 55 also found significant and higher odds of 1.60 times BP control in the intervention compared to the control group.These similarities could be due to the presence of respondents with controlled BP.In addition, the significance of BP control applying digital health intervention could also be due to the BP values at baseline in the studies included, which showed that those with inadequate BP control might also benefit from digital health intervention.Our findings provide evidence that digital health intervention could be an important strategy for BP control in LMICs.We found greater reductions both in SBP and DBP for studies conducted in UMIEs than in studies conducted in LMIEs.The finding affirmed a study by Mourtzinis et al., 56 that patients with hypertension in the lowest income quantile had a lower likelihood of achieving the BP target than those in the highest quantile.The reason may be that lower income was associated with a reduced likelihood of achieving BP control, 56 as a large proportion (31%) of households in low-income countries were unable to afford two BP-lowering medicines compared to 9% in middle-income countries and 1% in highincome countries. 57his systematic review shows that trials with interventions that lasted 12 months and beyond resulted in greater reductions in both SBP and DBP compared to studies that lasted less than 12 months.Our findings disagree with a study by Li et al., 19 who reported greater SBP reduction in studies that lasted less than 12 months.However, a study by Lu et al., 52 found no statistically significant reductions in SBP in studies with interventions that lasted less than 12 months.This implies that digital health interventions should be started as early as possible and sustained for a longer period.Although it is believed that 2009 was considered when digital health interventions began and were widely accepted, 16 of our subgroup meta-analyses showed that studies published after 2019 of digital health applications showed greater reductions in BP control compared to studies published before 2019.This could be attributed to the advancement in technology, which is altering the means healthcare services are provided, from wearable devices (BP monitors smartwatches, etc.) that deliver earlier diagnoses and treatment.
The wide accessibility and affordability of using mobile devices with SMS capacity reported in this review show the possible impact of a digital health intervention on lifestyle changes to reduce hypertensionrelated morbidity and mortality in LMICs.Studies have shown that digital health interventions result in changes in lifestyle behaviours as an effective tool for improving adherence, 55,58,59 which is consistent with the present review.In our meta-analysis, we found that digital health interventions showed significant effects for improvements in a healthy diet by reducing high salt intake.This finding concurs with the study by Kassavou et al., 55 who found positive effects for supporting improvements in a healthy diet by reducing the consumption of high-sodium food.Physical inactivity is independently associated with 12% of the global burden of hypertension. 51Thus, physical activity is measured as the basis on which changes in lifestyle to prevent cardiovascular disease must be based.Therefore, the finding in this meta-analysis is promising because the use of digital health interventions is seen to result in favourable changes in lifestyle behaviour such as physical activity, which can have a positive impact on the secondary prevention of future cardiovascular events. 60his finding is inconsistent with a study by Kassavou et al., 55 that found a moderate but insignificant effect of app-based behavioural self-monitoring interventions in improving physical activity.Our meta-analysis for smoking reduction revealed significant differences in the intervention compared to the control group.This finding agreed with the study by Kassavou et al., 55 that showed improvement in smoking cessation among those receiving an app-based self-monitoring intervention compared to those in the control group.Regarding the study by Kassavou et al., 55 only one study was found to report the percentage as significantly higher in the intervention group compared to the usual care group.
The effectiveness of digital health interventions on adherence to medication was reported in previous systematic reviews with an improvement in medication adherence and other health outcomes. 59,61,62Our metaanalysis showed that the digital health intervention of medication adherence increased the odds of achieving medication adherence twofold in the intervention group compared to the control group.Our finding is similar to the finding by Kassavou et al., 55 who found a significant effect of app-based behavioural self-monitoring interventions in supporting improvements in both BP and medication adherence.These findings are important because they provide us with confidence that digital health interventions could be effective solutions to support health behaviour change and thus reduce BP in patients treated for hypertension during BP checks or similar clinical consultations.
This review followed the PRISMA and Cochrane guidelines with enormous population demographics from 10 countries representing LMICs.Second, a sequence of sensitivity analyses was performed to determine the strength of the pooled estimates.Third, we reported on the reduction in BP, the percentage of respondents achieving controlled BP and the odds in the intervention compared to the control.However, this review also has limitations.First, only studies published in LMICs were considered, and only two articles from Africa were included because of our inclusion/exclusion criteria: digital health interventions in only patients with hypertension but not those with comorbidities such as diabetes or HMTOD were excluded.Second, some studies were found eligible for inclusion in LMICs, but the full texts were inaccessible after several efforts to contact the corresponding authors.Third, our review was based on published data, and therefore, we did not have access to the individual patient's data; hence, we were unable to conduct multiple imputations to take into account the missing data in the individual studies.It is possible that differences in the study methods might have influenced the studies' results.Fourth, the sequence of heterogeneity examined to determine possible causes, such as subgrouping the duration of digital health intervention, year of publication and countries' economic status, could not completely explain the details of heterogeneity.Furthermore, we did not have data on access to BP-lowering medicines, socioeconomic status, unavailability of public healthcare, and knowledge of hypertension, all of which could potentially influence the results; hence, they should be taken into consideration when interpreting these findings.Other limitations were that the review did not include grey literature or unpublished studies and considered only English publications.Regarding the comparable efficiency of phone calls, SMS and smartphone app interventions, the physicians consider digital health intervention decisions according to lifestyle modification because medication adherence was self-reported, which might have led to social desirability bias.
In conclusion, our review showed that digital health interventions may be effective in BP control, changes in lifestyle behaviours and improvements in medication adherence in LMICs.Only two studies were included in the review from Africa.The combination of digital health interventions with clinical management is crucial to achieving optimal clinical effectiveness in BP control, changes in lifestyle behaviours and improvements in medication adherence.Researchers globally should also aim to provide in detail the effectiveness and application of these interventions between patients and healthcare providers and the rate of reminders provided via digital health devices.

Fig. 1 :
Fig. 1: PRISMA flow chart of study selection.PRISMA flow diagram specifying the considerations to exclude and include the articles.
).Overall, participants receiving digital health intervention achieved a significant reduction in DBP [MD = −2.06mm Hg (95% CI −3.37 to −0.75); n = 8688] compared with the control.The reduction difference between the interventions and usual care was statistically significant in the combined effect (mobile phone calls, SMS and smartphone app studies) and each of the three individual methods of providing mHealth interventions.SMS interventions showed the highest DBP reduction compared with the control (MD = −3.02mm Hg [−4.25 to −1.79]; n = 6931), followed by smartphone apps (MD = −1.15mm Hg [−4.09 to 1.78]; n = 1489) and mobile phone calls

Fig.
Fig.2: Forest plot of the mean difference in SBP between the intervention and control groups.Forest plot of mean difference in systolic blood pressure (SBP) (expressed as mm Hg) between the digital health intervention and the control groups, and subgroup analysis by mode of delivery of the intervention (Mobile phone call, Short message service (SMS) and Smartphone app).The size of the blue squares indicates the weight of the evidence from each of the studies.Studies with CI (horizontal line) crossing zero (vertical line) are inconclusive.Studies with more participants have narrower CIs.The red diamonds represent the summary effect sizes in each of the subgroups and the green the overall sample, with the width of the diamond indicating the 95% CI.A statistically significant greater reduction in SBP is seen in the intervention group, compared with the control group in the overall sample and with the two modes of delivery (SMS and smartphone app).SMS interventions displayed the greatest reduction, compared with smartphone apps and mobile phone calls, but the differences between the three modes were not significant.The data present high heterogeneity.

Fig. 3 :
Fig. 3: Meta-analysis of dichotomous outcome measurements for BP control.Forest plot of odds ratio in blood pressure (BP) control between the digital health intervention and the control groups.The size of the blue squares indicates the weight of the evidence from each of the studies.Studies with CI (horizontal line) crossing zero (vertical line) are inconclusive.Studies with more participants have narrower CIs.The black diamonds represent the summary effect sizes in the overall sample, with the width of the diamond indicating the 95% CI.A statistically significant greater reduction in BP is seen in the intervention group, compared with the control group.The data present high heterogeneity.

Fig. 7 :
Fig.7: Meta-analysis of continuous outcome measurements for adherence to medication.Forest plot of standard mean difference for continuous outcome measurements for adherence to medication between the digital health intervention and the control groups.The size of the green squares indicates the weight of the evidence from each of the studies.Studies with CI (horizontal line) crossing zero (vertical line) are inconclusive.The black diamonds represent the summary effect sizes in the overall sample, with the width of the diamond indicating the 95% CI.A statistically significant greater reduction in adherence to medication is seen in the intervention group, compared with the control group.The data present high heterogeneity.

Fig. 8 :
Fig.8: Meta-analysis of dichotomous outcome measurements for adherence to medication.Forest plot of standard mean difference for dichotomous outcome measurements for adherence to medication between the digital health intervention and the control groups.The size of the blue squares indicates the weight of the evidence from each of the studies.Studies with CI (horizontal line) are inconclusive.The black diamonds represent the summary effect sizes in the overall sample, with the width of the diamond indicating the 95% CI.A statistically significant greater reduction in adherence to medication is seen in the intervention group, compared with the control group.The data present moderate heterogeneity.

Table 1 :
Characteristics of the included study interventions and outcomes.
names, publication year, study details (country, design, masking and randomization method, retention rate, and statistical analyses), participants' characteristics (condition, inclusion and exclusion criteria, sample size, Supplementary File, TableS3on pages17-18).Age was grouped for subgroup analysis in this review based on the WHO's report that an estimated 1.28 billion adults aged 30-79 years (average 54 years) worldwide have hypertension, the majority of whom (two-thirds) live in LMICs, 2 in the Supplementary File, TableS4, on pages 22-23).CG: control group; IG: intervention group; RCT: randomized control trial; SMS: short message service; Δ: change; SBP: systolic blood pressure; DBP: diastolic blood pressure; BP: blood pressure; OR: odds ratio; RR: relative risk; DASH: dietary approaches to stop hypertension; AMD: adjusted mean difference; 8-item MMAS score: 8-item Morisky Medication Adherence Scale score; PA: physical activity; BMI: body mass index; LDL-C: low-density lipoprotein-cholesterol.